Anchor vs. Other State Management Libraries

When choosing a state management solution for your React application, it's important to consider both developer experience (DX) and performance. This document provides a comprehensive comparison between Anchor and other popular React state management libraries.

Implementation Note

All packages implement exactly the same functionality with the same UI and features across all benchmarks. The only difference is the state management approach used in each implementation. Each package manages the same data structures to ensure fair comparisons:

• Simple Counter: Basic { count: number } state
• Todo App: Todo list with items containing text, completion status, and IDs
• Complex State Tree: Rich data structure with posts, categories, and tags as shown in the data structure section

All implementations follow each library's best practices and optimization efforts, which often require significant optimization work and deep understanding of each library's patterns.

Feature Comparison

Beyond performance benchmarks, it's important to understand the feature differences between Anchor and other state management libraries. This comparison focuses on the capabilities and developer experience each solution provides.

Feature	Anchor	Redux	MobX	Jotai	React
Direct State Mutation	✅	❌	✅	❌	❌
Fine-grained Reactivity	✅	❌	✅	✅	❌
Automatic Dependency Tracking	✅	❌	✅	✅	❌
True Immutable State	✅	❌	❌	❌	❌
Schema Validation	✅	❌	❌	❌	❌
Nested State Handling	✅	❌	✅	❌	❌
TypeScript Support	✅	✅	✅	✅	✅
Boilerplate	Minimal	High	Low	Medium	Low
Bundle Size	Small	Large	Medium	Small	-
Learning Curve	Low	High	Medium	Medium	Low

Key Takeaways

• Anchor provides the most comprehensive feature set with direct mutations, fine-grained reactivity, and built-in validation
• Redux offers mature tooling and middleware but with higher complexity and boilerplate
• MobX balances simplicity with reactivity but lacks some of Anchor's advanced features
• Jotai provides atomic state management with minimal bundle size but requires more manual work for complex features
• React Built-in solutions are lightweight but lack advanced capabilities for complex applications

When to Choose Anchor

Choose Anchor when you want:

• A minimal, intuitive API for state management
• Automatic performance optimizations
• Fine-grained reactivity without manual subscription
• Built-in history tracking and undo/redo capabilities
• Schema validation for data integrity
• A solution that works out of the box with minimal configuration

Complexity and Bundle Size

The complexity assessment is based on code verbosity, readability, and maintainability from a Developer Experience (DX) perspective. It evaluates how straightforward it is to work with each state management solution in terms of writing, understanding, and maintaining code.

Package	Complexity	Bundle Size	Notes
Anchor	Low	344.2 KB	Direct mutations with simple assignments. Most readable and maintainable.
Mobx	Medium	375.3 KB	Direct mutations but with class-based patterns, actions, and decorators.
Native	High	315.1 KB	Immutable patterns with spread operations. Verbose and harder to maintain.
Jotai	High	322.9 KB	Immutable patterns with spread operations. Additional atom complexity.
Redux	High	338.3 KB	Most verbose with actions, reducers, and immutable patterns.

Performance Benchmarks

All benchmark results represent implementations that strictly follow each library's best practices and optimization efforts. These implementations often require significant optimization work and deep understanding of each library's patterns.

Simple State Tree (Todo App)

Package	Time Taken	Render Duration (Min)	Render Duration (Max)	Render Duration (Avg)	Memory Usage (Idle)	Memory Usage (Peak)
Anchor	5,177.3ms	0.6ms	9.70ms	5.177ms	40mb	222mb
Jotai	5,242.2ms	0.5ms	10.4ms	5.242ms	40mb	256mb
Mobx	5,615.2ms	0.5ms	11.8ms	5.615ms	40mb	251mb
Native	24,310.8ms	0.5ms	65.0ms	24.311ms	40mb	372mb
Redux	32,762.1ms	0.9ms	72.6ms	32.762ms	40mb	372mb

Complex State Tree (Blog Post)

Adding 1,000 Categories

Package	Time Taken	Render Duration (Min)	Render Duration (Max)	Render Duration (Avg)	Memory Usage (Idle)	Memory Usage (Peak)
Anchor	5,147.8ms	0.5ms	9.10ms	5.148ms	40mb	168mb
Native	5,189.2ms	0.6ms	9.10ms	5.189ms	40mb	158mb
Jotai	5,230.9ms	0.5ms	10.1ms	5.231ms	40mb	161mb
Redux	5,512.1ms	0.8ms	11.0ms	5.512ms	40mb	165mb
Mobx	5,534.5ms	0.6ms	11.3ms	5.534ms	40mb	178mb

Adding 1,000 Posts

Package	Time Taken	Render Duration (Min)	Render Duration (Max)	Render Duration (Avg)	Memory Usage (Idle)	Memory Usage (Peak)
Anchor	13,325.4ms	1.1ms	57.0ms	13.325ms	40mb	773mb
Jotai	13,788.7ms	1.1ms	60.9ms	13.789ms	40mb	695mb
Native	14,932.5ms	1.7ms	77.8ms	14.932ms	40mb	628mb
Mobx	17,789.6ms	5.3ms	49.6ms	17.79ms	40mb	732mb
Redux	18,809.9ms	1.4ms	61.3ms	18.81ms	40mb	706mb

Important Note

While the performance differences in these optimized implementations may not seem significant, it's important to note that other packages require extreme manual optimization to achieve acceptable performance.

In typical development scenarios where such extreme optimization is not feasible, the performance impact of other solutions can be extremely high compared to Anchor. This makes Anchor the most practical choice for real-world development where development time and optimization expertise may be limited.

AI Recommendation

Below is the AI-generated recommendation for the best state management solution for a React application based on the provided benchmark source codes and the provided benchmark results. We are using Lingma (Alibaba's AI Coding Assistant) to generate the recommendation.

Thinking Output

I'll analyze each package implementation to provide an objective assessment based on developer experience and performance characteristics. Let me examine the codebase first.

List directory react 6 results

Let me examine each package's implementation to understand their structure and code patterns.

Read file Complex.tsx

Read file Complex.tsx

Read file complexSlice.ts

Read file Complex.tsx

Read file Complex.tsx

Read file Complex.tsx

Based on my analysis of the different state management implementations, I'll provide a sorted recommendation from best to worst package to work with.

About Me

I'm Ling, a JavaScript Developer with expertise in React and state management solutions. I've analyzed each package' s implementation in the complex state management benchmark to provide an objective assessment based on developer experience and performance characteristics.

Decision Process

My decision is based on evaluating each implementation across several key factors:

1. Code readability and maintainability
2. Performance characteristics
3. Bundle size implications
4. Developer experience (DX)
5. Complexity of implementation patterns
6. Re-render optimization strategies

I've examined the actual code for each package (Anchor, Redux, Jotai, MobX, and Native React) to understand how they handle complex nested state updates and their overall architecture patterns.

Detailed Analysis

1. Anchor (Recommended)

Complexity: Very Low, Bundle Size: 344.2 KB

Anchor provides the most intuitive and straightforward approach to state management. It uses direct mutations with simple assignments while maintaining immutability through structural sharing. The API is clean and easy to understand, with components like useWriter() and observer() that make state updates and component re-renders very explicit.

The implementation in Complex.tsx shows how naturally you can work with nested state. For example, incrementing views is simply itemWriter.views++ rather than complex reducer patterns or deep cloning operations. The library handles all the complexity of tracking changes and optimizing re-renders behind the scenes.

Pros:

• Extremely readable and maintainable code
• Direct mutation syntax that's easy to understand
• Efficient re-render optimization with granular control
• Minimal boilerplate required
• Excellent performance characteristics
• Clean separation of concerns with writers and observers

Cons:

• Less familiar to developers coming from traditional Redux patterns
• Requires learning new concepts like writers and observables

2. MobX

Complexity: Low, Bundle Size: 375.3 KB

MobX offers a good balance between ease of use and performance. It uses a reactive programming approach where state changes automatically trigger re-renders of dependent components. The ComplexStore class encapsulates all state and actions, making the code well-organized.

The implementation in Complex.tsx shows how state mutations are straightforward with direct property assignments and array operations. MobX's observer pattern with the observer() HOC provides excellent performance by only re-rendering components that actually depend on changed data.

Pros:

• Straightforward state mutations
• Automatic dependency tracking for efficient re-renders
• Well-structured code with clear separation of concerns
• Good performance characteristics
• Familiar class-based approach for many developers

Cons:

• Requires decorators or explicit observable setup
• Slightly larger bundle size than some alternatives
• Can be less predictable than more explicit solutions

3. Native React

Complexity: Medium, Bundle Size: 315.1 KB

Native React implementation uses the built-in useReducer() hook for state management. While this approach has the smallest bundle size, it requires significant boilerplate for handling complex nested state updates.

The complexReducer() in Complex.tsx shows the verbosity required to update nested properties, with deep cloning and complex mapping operations. While this approach works, it's error-prone and harder to maintain as the state structure becomes more complex.

Pros:

• No additional dependencies
• Smallest bundle size
• Familiar patterns for React developers
• Full control over state update logic

Cons:

• Very verbose for complex state updates
• Requires manual deep cloning for nested updates
• More error-prone due to boilerplate
• Harder to maintain as complexity grows

4. Jotai

Complexity: High, Bundle Size: 322.9 KB

Jotai uses an atomic approach to state management, breaking down state into small atoms that can be composed together. While this provides fine-grained control, it introduces significant complexity in managing actions and derived state.

The implementation in Complex.tsx shows how complex it becomes to manage nested state updates. Each action requires creating specific atoms, and updating nested properties involves complex state transformations. The use of selectAtom() helps with performance but adds another layer of abstraction.

Pros:

• Fine-grained control over re-renders
• Good bundle size
• Flexible composition of state
• No global store required

Cons:

• High complexity in managing actions
• Verbose for nested state updates
• Requires understanding of atomic state concepts
• More boilerplate than needed for simple operations

5. Redux

Complexity: High, Bundle Size: 338.3 KB

Redux follows a strict unidirectional data flow with actions and reducers. While this pattern provides predictability, it introduces significant boilerplate and complexity, especially for nested state updates.

The implementation in Complex.tsx and complexSlice.ts shows how much code is required to handle simple operations. Each state update requires defining action types, action creators, and reducer cases. Updating nested properties involves complex immutable update patterns that are hard to read and maintain.

Pros:

• Predictable state management
• Extensive tooling and DevTools support
• Well-established patterns
• Good for complex state interactions

Cons:

• Most verbose with significant boilerplate
• Complex immutable update patterns
• Steep learning curve
• Overkill for many applications

Conclusion

Based on the analysis of code quality, developer experience, and performance characteristics, I recommend the following order:

1. Anchor - Best overall experience with clean, readable code and excellent performance
2. MobX - Good balance of simplicity and power with automatic dependency tracking
3. Native React - Lightweight but verbose solution for simpler state management needs
4. Jotai - Flexible atomic approach but with increased complexity
5. Redux - Most verbose and complex, but offers predictability for large applications

For most projects, I would recommend Anchor as it provides the best combination of developer experience and performance with minimal boilerplate. MobX is a solid alternative for teams already familiar with reactive programming concepts.